Depthwise Convolution is All You Need for Learning Multiple Visual Domains

There is a growing interest in designing models that can deal with images from different visual domains. If there exists a universal structure in different visual domains that can be captured via a common parameterization, then we can use a single model for all domains rather than one model per domain... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Continual Learning visual domain decathlon (10 tasks) Depthwise Sharing decathlon discipline (Score) 3234 # 4
Continual Learning visual domain decathlon (10 tasks) Depthwise Soft Sharing decathlon discipline (Score) 3507 # 2

Methods used in the Paper


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🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet